杜子豪,操日亮,赵一平

背景：消防救援人员长期在高危、高压的极端作业环境里工作。其身心长期承受高负荷运转，生理疲劳累积，心理创伤应激引发的综合损伤风险，这已经成了制约应急救援队伍战斗力和个体远期健康的关键问题。目的：本综述要系统地探究多模态数据融合技术在消防员职业心理创伤筛查里的应用价值，深入评估基于可解释人工智能（AI）的预测模型与沉浸式虚拟现实（VR）协同干预机制的临床有效性。方法：本文对近年来消防员生理疲劳、步态变异、创伤后应激障碍（PTSD）以及职业倦怠的流行病学特征进行了综合分析。并且，系统对可穿戴多模态传感监测技术、集成机器学习算法以及虚拟现实暴露疗法（VRET）的最新实证研究进行了梳理。结果：高强度的实战任务会明显改变消防员的生物力学步态特征，还会增加跌倒风险。在心理方面，职业倦怠和睡眠障碍是导致并加重PTSD的关键中介因素。借助深度耦合步态学特征、生理反馈以及心理评估数据，再用贝叶斯网络或者超图神经网络这类机器学习模型，就能很好地达成身心损伤风险的早期动态精准预警。另外，沉浸式VR与现实物理任务的自适应干预机制，把传统单一治疗的局限给打破了。结论：融合“人工智能多模态筛查+身心一体化VR康复”的范式，给高危职业人群提供了数据驱动的智能预警和精准干预工具，临床转化和职业健康保障价值很明显。

消防救援人员；职业心理创伤；多模态融合；可解释人工智能；虚拟现实暴露疗法；步态分析；职业倦怠；创伤后应激障碍

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